A tri-level coordination strategy for coupled power and transportation systems based on hierarchical rolling optimization: integrating individual EV dispatch with network management

The intensive travel and charging demands of electric vehicles (EVs) pose new challenges to the coordinated operation of the transportation network (TN) and power distribution network (PDN). Existing centralized EV charging scheduling approaches fail to capture the flexible charging durations of private car users and the time-sensitive charging requirements of taxi drivers. Moreover, with the widespread adoption of fast-charging stations, charging decisions within stations have become increasingly diversified. Accordingly, this paper integrates the optimization of the coupled power distribution and transportation system with individual EV charging scheduling, proposing a three-level rolling optimization iterative model that incorporates the dynamic evolution characteristics of the TN to optimise the interests of multiple stakeholders in the coupled system. For vehicles with charging demands, the lower-level model formulates a two-stage optimization problem that uses electricity price signals from the middle level to compute the cumulative cost function (CCF) and minimize the overall cost of EVs. In the middle-level model, The PDN performs optimal power flow calculations based on partitioning results and the distribution locational marginal price (DLMP), formulates dynamic incentive electricity prices to encourage decision-making by both the corresponding levels of energy storage systems (ESS) and EVs. The upper-level ESS model optimizes the output of ESS resources based on the electricity price information provided by the middle level, minimizing operational costs. This paper validates the proposed method using real TN and POI distributions from real urban area. The results indicate that the proposed method reduces EVs' charging costs, ensures ESS revenue, and minimizes PDN operational costs under limited EV scheduling.